Treatment guidance based on victim circulatory status and prior shock outcome

ABSTRACT

A system for managing care of a person receiving emergency cardiac assistance is disclosed that includes one or more capacitors for delivering a defibrillating shock to a patient; one or more electronic ports for receiving signals from sensors for obtaining indications of an electrocardiogram (ECG) for the patient; and a patient treatment module executable on one or more computer processors to identify a phase in which a patient being monitored by the system is in relative to a time at which an adverse cardiac event for patient began.

CLAIM OF PRIORITY

This application claims priority under 35 USC §119(e) to U.S. PatentApplication Ser. No. 61/784,139, filed on Mar. 14, 2013, U.S. PatentApplication Ser. No. 61/834,737, filed on Jun. 13, 2013, and U.S. PatentApplication Ser. No. 61/933,063, filed on Jan. 29, 2014, the entirecontents of which are hereby incorporated by reference.

TECHNICAL FIELD

This document relates to cardiac resuscitation systems and techniques.

BACKGROUND

Heart attacks are a common cause of death. A heart attack occurs when aportion of the heart tissue loses circulation and, as a result, becomesdamaged (e.g., because of blockage in the heart vasculature). Heartattacks and other abnormalities can lead to ventricular fibrillation(VF), which is an abnormal heart rhythm (arrhythmia) that causes theheart to lose pumping capacity. If such a problem is not correctedquickly—typically within minutes—the rest of the body loses oxygen andthe person dies. Therefore, prompt care of a person undergoingventricular fibrillation can be key to a positive outcome for such aperson.

One common way to treat ventricular fibrillation is through the use ofan electrical defibrillator that delivers a relatively high voltageshock to the heart in order to force it back to a normal, consistent,and strong rhythm. People who have had previous problems withventricular fibrillation may be implanted with an automaticdefibrillator that constantly monitors the condition of their heart andapplies a shock when necessary. Other such people may be provided with awearable defibrillator in the form of a vest such as the LIFEVESTproduct from ZOLL medical Corporation. Other people may be treated usingan external defibrillator, such as in a hospital or via an automaticexternal defibrillator (AED) of the kind that is frequently seen inairports, public gymnasiums, and other public spaces. Defibrillation maybe delivered in coordination with cardiopulmonary resuscitation, whichcenters around the provision of repeated compressions to a victim'schest, such as be a rescuer pressing downward repeatedly with the palmsof the hands, or via a mechanical compression device such as theAUTOPULSE non-invasive cardiac support pump from ZOLL MedicalCorporation.

People undergoing ventricular fibrillation may be more receptive to adefibrillating shock in some instances compared to others. For example,research has determined that a indication of whether a shock that isdelivered will likely result in successful defibrillation can beobtained using a computation of amplitude spectrum area (AMSA), or othercomputational methods that use either time-based or spectrum-basedanalytic methods to calculate, from an electrocardiogram (ECG), aprediction of defibrillation shock success.

SUMMARY

This document describes systems and techniques that may be used to helpdetermine when a shock on a person suffering from VF will likely besuccessful, i.e., will defibrillate the person. Such systems andtechniques may also be used to determine where, time-wise, a person isin the process of suffering from cardiac arrest and fibrillation, sincedefibrillating shocks may be much less effective after a person has beenfibrillating for several minutes, and CPR (including forceful CPR) maybe a preferred mode of treatment instead. Techniques for making suchpredictions more accurately are also described herein.

Such determinations may then be used to guide someone (e.g., aphysician, EMT, or lay rescuer) who is performing rescue operations onthe person suffering VF (also referred to here as a patient or victim),such as by a portable defibrillator providing an indication, on agraphical display of the defibrillator or another device or audibly,that a shock should or should not be provided, or that chestcompressions of a particular type should be given instead of a shock.Also, a device may display an estimated time since the fibrillationsbegan so as to provide further information to a rescuer. Inimplementations described below, for example, such systems andtechniques may take into account the success or lack of success in priorattempts to defibrillate the person (e.g., where there has beenrecurrent or refractory VF—where recurrent VF results after a successfulprior defibrillating shock and refractory VF results after anunsuccessful prior defibrillating shock), among other factors, such as acurrent AMSA value for the person and trans-thoracic impedance level ofthe person.

Such systems may also take into account a current AMSA value (e.g., forrecommending a shock) in combination of a trend in AMSA value over time(e.g., for recommending chest compressions instead of a shock). AMSA isa value calculated by taking a Fast Fourier Transform (FFT) of the VFwaveform. While FFTs are generally premised on an assumption of aninfinitely long time series, relatively short time series (e.g., lessthan 4 seconds and more preferably close to 1 second) may be better forpredicted a likelihood of defibrillation. But short windows aregenerally inimical to proper operation of an FFT. As described below, atapered window, such as a Tukey window, may be used to lessen edgeeffects from the windowing of ECG data that is collected for performingthe AMSA calculation, which may permit the relative benefits of using asmaller window while lessening the dis-benefits of using the smallerwindow.

As one example of using AMSA values to make a determination of thelikelihood that a currently-delivered shock with result in successfuldefibrillation, a threshold AMSA value may be set, at which level theshocking ability of a defibrillator is made available to a rescuer, orat which a likelihood of success that is displayed to the rescuer maychange (e.g., AMSA values between X and Y may show a likelihood of mpercent, while AMSA values between Y and Z may show a likelihood valueof n percent) based on whether prior successful defibrillating shocksthat have been given to a patient have been successful. For example, therelevant AMSA threshold for generating a certain output or action of adefibrillator (such as the display to the user just mentioned) may beadjusted based on determinations about the success of prior shocks andon the trans-thoracic impedance.

Thus, for example, an AMSA value or values may be computed from incomingECG signals from the person, and decisions may be made by comparing thecomputed AMSA value to stored thresholds, where the thresholds maychange based on the other factors, or the AMSA value may be adjustedusing the other factors and then be compared to thresholds that do notchange. Generally, there is no practical difference between changing thevalue and making static the thresholds against which it is comparedversus changing the thresholds and leaving the value set.

Such adjustments, when based on determinations about the success or lackof success of prior defibrillation efforts, may be made in a variety ofways. For example, AMSA threshold values (which are reduced forrecurrent VF) associated with future successful defibrillation have beendetermined to fall substantially when there has been a prior successfuldefibrillation during an emergency with a particular patient. (Unlessindicated otherwise, all values that are collected, computed, andcompared here are for a single adverse cardiac event for a patient.)

Such correlations may be determined by analysis of historicaldefibrillation activity (e.g., collected by portable defibrillatorsdeployed in the field for actual cardiac events), and may be used toproduce a mapping between observed past likelihood of success forvarious AMSA values and levels of prior successful defibrillations. Suchdata may be used, for example, to generate a look-up table or similarstructure that can be loaded on other deployed (e.g., via network and/orwireless data updates) or to-be-deployed defibrillators, which can beconsulted in the future during other cardiac events. For example, thenumber of prior successful defibrillations for an event may be along oneaxis of a table, and an AMSA score may be along another, and those otherdefibrillators may employ both values for a victim, with the tableproducing an indication of a likelihood of a to-be-applied shock beingsuccessful. The table or other data structure may also have additionaldimensions, such as a dimension that identifies trans-thoracicimpedance, and dimensions that identify other variables whose valuesthat have been determined to be relevant to whether an applied shockwill likely be successful.

As noted, a tapering function may be applied to the ECG data, so as toimprove the accuracy of the FFT applied to the data, by preventing thedata from jumping immediately from a zero value up the measured values,and then back down immediately to a zero value at the end of a measuredwindow. Various parameters for the tapering function may also beapplied, such as coefficients to define the slops of the starting andending edges of the function. The particular type of tapering functionused and the coefficients applied to it may be determined by analysis ofECG data and shock outcomes from prior rescue efforts that have beensensed and stored by on-site monitors (e.g., as part of portabledefibrillators), and analyzed after-the-fact as a group to identifycorrelations between particular AMSA values, window sizes, windowshapes, and defibrillation outcomes.

In certain other implementations, multiple different tapering functionsmay be applied to the same data essentially simultaneously, and theresulting AMSA value from one of the functions may be selected, or anAMSA value may be generated that is a composite from multiple differenttapering functions. The window function that is used, the length of thewindow, and the coefficients for the window may also be adjusteddynamically, so that one or more of them change during a particularincident, or deployment, with a particular patient. For example, it maybe determined from analysis of prior data that a certain window shape,size, and/or coefficients are better earlier in an episode of VF thanlater, so that a defibrillator may be programmed to change suchparameters over the course of an event. Such changes may be tied to aninitial determination about how long the patient has been in VF, whichmay be a function of user input (e.g., when the emergency call was made)and parameters measured by the defibrillator. Also, changes to thewindow type, size, and coefficients may be made from readingsdynamically made from the patient under treatment. For example, AMSAvalues in a particular range may be measured better by a particularwindow type, size, or range of coefficients, so that an AMSA measurementmade at time n that shows such a value, may be measured using the otherparameters known to work best with that AMSA value at time n+1. Othertechniques for dynamically adjusting the window type, window size,and/or coefficients may also be employed. The shape of the window may beasymmetric. For instance, the edge of the window that is “older” in timemay have a window shape that results in a greater level of attenuationthat the “newer” portion of the windowed data.

Upon a defibrillator making a determination of a likelihood of futuresuccess for defibrillating a patient, the defibrillator may provide anindication to a rescuer about such a determination. For example, thedefibrillator may only allow a shock to be performed when the indicationis sufficiently positive (e.g., over a set percentage of likelihood ofsuccess)—and may only provide a “ready for shock” light or otherindication in such a situation. Also, a defibrillator may provide adisplay—such as a graphic that shows whether defibrillation will likelysucceed (e.g., above a predetermined threshold level of likelihood ofsuccess) or provide a number (e.g., a percentage of likelihood ofsuccess) or other indication (e.g., a grade of A, B, C, D, or F) so thatthe rescuer can determine whether to apply a shock. In some situations,the AMSA value may serve merely to provide a recommendation to the user,with the user able to apply a shock at any time; in other situations(e.g., especially for AEDs to be used by lay rescuers), the AMSA valuemay be used to disable or enable the ability to deliver a shock.

The device (e.g., defibrillator) can also change the indication itpresents in different situations, e.g., a dual-mode defibrillator couldsimply indicate whether defibrillation is advised (and may refuse topermit delivery of a shock when it is not advised) when thedefibrillator is in AED mode, and may provide more nuanced informationwhen the defibrillator is in manual mode, and thus is presumably beingoperated by someone who can better interpret such nuanced informationand act properly on it.

With respect to indications of where a victim is in the process of a VFepisode—e.g., how many minutes since the victim's episode has started—anaverage AMSA value may be determined over a time period so as toidentify more generalized changes in the victim's AMSA values, ratherthan AMSA at a particular point in time or small slice of time. Forexample, AMSA values can be computed for particular points in time orparticular windows in time and those values can be saved (e.g., inmemory of a patient monitor or defibrillator). After multiple suchmeasurements and computations have been made, an average may be computedacross multiple such values. Because AMSA generally falls (on average)over time in an episode, if the average for a certain number of readings(e.g., a moving average) falls below a particular value or falls belowthe value over a minimum time period (so as to indicate the general AMSAcondition of the victim rather than just a transient reading), thedevice may provide additional feedback to a rescuer.

These general phases of cardiac arrest or VF may be identified, in onerepresentation, as three separate phases (though there may be someoverlap at the edges of the phases): electrical, circulatory, andmetabolic. The electrical phase is the first several minutes of anevent, and marks a period during which electric shock can beparticularly effective in defibrillating the victim's heart andreturning the victim to a relative satisfactory condition. Thecirculatory phase appears to mark a decrease in effectiveness forelectric shock in defibrillating the victim, and particularly in theabsence of chest compressions performed on the victim. As a result, adevice such as a portable defibrillator may be programmed to stopadvising shocks during such a phase (or may advise a shock only whenother determinations indicate that a shock would be particularly likelyto be effective) and may instead advise forceful CPR chest compressions.Such forceful compressions may maximize blood flow through the hearttissue and other parts of the body so as to extend the time that thevictim may survive without lasting or substantial damage.

In the metabolic phase, chest compressions may be relatively ineffectiveas compared to the circulatory phase. For example, where tissue hasbecome ischemic, such as in circulatory phase, the tissue may reactfavorably to the circulation of blood containing some oxygen, but wheretissue has become severely ischemic, such as in metabolic phase, theintroduction of too much oxygen may be harmful to the tissue. As aresult, more gentle compressions for the first period, such as 30seconds, may need to be advised in the metabolic phase before therescuer (or a mechanical chest compressor controlled to provideappropriate levels of compression following the points addressed here)uses a full force.

Other treatments that may be useful in the metabolic phase includeextracorporeal circulation and cooling, either alone, in combinationwith each other, or in combination with other pharmacologicaltreatments. In any event, observation of elapsed time since an event hasbegun and/or observation of the phase in which a victim is in, may beused to control a device or instruct a rescuer to switch from a firstmode of providing care to a second mode of providing care in which theparameters of the provided care differ (e.g., speed or depth of chestcompressions may change, temperature-based therapy may be provided orstopped, or pharmaceuticals may be administered).

In certain implementations, such systems and techniques may provide oneor more advantages. For example, determinations of whether a shockshould be provided or what advice to provide a rescuer based on thephase a victim is in can be made from values that are already beingmeasured for a patient (e.g., trans-thoracic impedance may already beused by a defibrillator to affect the shape of the voltage of thewaveform that is provided to the patient). For example, determinationsabout shocks may be improved compared to simply measuring AMSA, and maythus result in better performance for a system and better outcomes for apatient. In particular, a defibrillator may cause a rescuer to wait toprovide a defibrillating shock until a time at which the shock is morelikely to be effective. As a result, the patient may avoid receiving anineffective shock, and then having to wait another cycle for anothershock (which may end up being equally ineffective). And a system mayguide the rescuer in providing a shock, versus providing deep chestcompressions, versus providing progressive chest compressions (or maycause a device to provide such actions automatically), throughout thecourse of a cardiac event. Such a process may, therefore, result in thepatient returning to normal cardiac function more quickly and with lessstress on his or her cardiac system, which will generally lead to betterpatient outcomes.

The use of particular type, duration, and coefficients for making AMSAreadings may result in more accurate instructions being given to a humanor mechanical rescuer, or in enabling or disabling functionality of amedical device. In particular, the feedback provided may result indeterminations about whether to shock or not shock, or to provide chestcompressions, may be more closely aligned with a likelihood of apositive outcome (e.g., defibrillation) for a particular patient, andmay be customized to the present situation of the patient (e.g., asindicated by AMSA readings for the patient).

In one implementation, a system for managing care of a person receivingemergency cardiac assistance is disclosed. The system comprises one ormore capacitors for delivering a defibrillating shock to a patient; oneor more electronic ports for receiving signals from sensors forobtaining indications of an electrocardiogram (ECG) for the patient; anda patient treatment module executable on one or more computer processorsto provide a determination of a likelihood of success from delivering afuture defibrillating shock to the person with the one or morecapacitors, using (a) information about a prior defibrillating shock,and (b) a value that is a function of current ECG signals from thepatient. The system can also include an output mechanism arranged toindicate, to a user of the system, an indication regarding thelikelihood of success from delivering a defibrillating shock to theperson with the one or more capacitors. The output mechanism can includea visual display, and the system can be programmed to display to theuser one of multiple possible indications that each indicate a degree oflikelihood of success. Alternatively or in addition, the outputmechanism can comprise an interlock that prevents a user from deliveringa shock unless the determined likelihood of success exceeds a determinedvalue.

In some aspects, the patient treatment module comprises an ECG analyzerfor generating an amplitude spectrum area (AMSA) value, wherein thepatient treatment module uses the information about the level of successfrom the prior defibrillating shock to adjust the AMSA value. Moreover,the patient treatment module can comprise an ECG analyzer for generatingindications of heart rate for the patent, heart rate variability for thepatent, ECG amplitude for the patent, and/or first or second derivativesof ECG amplitude for the patent. The indication of ECG amplitude cancomprise, for example, an RMS measurement, measure peak-to-peak,peak-to-trough, or an average of peak-to-peak or peak-to-trough over aspecified interval

In other aspects, the patient treatment module is programmed todetermine whether a prior defibrillation shock was at least partiallysuccessful, and based at least in part on the determination of whetherthe prior defibrillation was at least partially successful, modify acalculation of the likelihood of success from delivering the futuredefibrillating shock. Moreover, determining a likelihood of success fromdelivering a future defibrillating shock to the person can depend on adetermination of whether one or more prior shocks delivered to theperson were successful in defibrillating the person. In addition,determining a likelihood of success from delivering a futuredefibrillating shock can comprise performing a mathematical transform onthe ECG data. The mathematical transform can be selected from a groupconsisting of Fourier, discrete Fourier, Hilbert, discrete Hilbert,wavelet, and discrete wavelet methods. In addition, determining alikelihood of success from delivering a future defibrillating shockcomprises performing a calculation by an operation selected from a groupconsisting of logistic regression, table look-up, neural network, andfuzzy logic.

In yet another example, the patient treatment module is programmed todetermine the likelihood of success from delivering a futuredefibrillating shock using at least one patient-dependent physicalparameter separate from a patient ECG reading. The patient treatmentmodule can also be programmed to determine the likelihood of successfrom delivering a future defibrillating shock using at a measure oftrans-thoracic impedance of the person.

In another implementations, a method for managing care of a personreceiving emergency cardiac assistance is disclosed, and comprisesmonitoring, with an external defibrillator, electrocardiogram (ECG) datafrom a person receiving emergency cardiac assistance; determiningwhether a prior defibrillation shock occurred; determining a likelihoodof future defibrillation shock success using at least the ECG data;based at least in part on the determination of whether the priordefibrillation occurred, modifying the calculation of the chance ofdefibrillation shock success; and affecting control of the externaldefibrillator based on the identification of whether a presentdefibrillation shock will likely be effective. Determining a likelihoodof future defibrillation shock success can comprise determining a valuethat is a function of electrocardiogram amplitude at particulardifferent frequencies or frequency ranges. Determining a likelihood offuture defibrillation shock success can comprise determining anamplitude spectrum area (AMSA) value for the ECG data, and can alsocomprise adjusting the determined AMSA value using information about theprior defibrillation shock. In addition, the method can comprisedetermining whether the adjusted AMSA value exceeds a predeterminedthreshold value.

In certain aspects, the method comprises providing to the rescuer avisual, audible, or tactile alert that a shockable situation exists forthe person, if the adjusted AMSA value is determined to exceed thepredetermined threshold value. The method can also include determiningwhether a prior defibrillation shock was at least partially successful,and based at least in part on the determination of whether the priordefibrillation was at least partially successful, modifying acalculation of the likelihood of success from delivering the futuredefibrillating shock. The determining of a likelihood of success fromdelivering a future defibrillating shock can comprise performing amathematical transform on the ECG data, and the mathematical transformmay be selected from a group consisting of Fourier, discrete Fourier,Hilbert, wavelet, and discrete wavelet methods. Also, determining alikelihood of success from delivering a future defibrillating shock cancomprise performing a calculation by an operation selected from a groupconsisting of logistic regression, table look-up, neural network, andfuzzy logic. Moreover, the likelihood of success from delivering afuture defibrillating shock can be determined using at least onepatient-dependent physical parameter separate from a patient ECGreading.

In certain other aspects, the additional physiologic parameter istrans-thoracic impedance of the person receiving emergency cardiac care,and the indication of trans-thoracic impedance can be determined fromsignals sensed by a plurality of electrocardiogram leads that alsoprovide the EGO data. The method may also include cyclically repeatingthe actions of monitoring, determining, identifying and providing theindication. The method also can comprise identifying compression depthof chest compressions performed on the person, using a device on theperson's sternum and in communication with the external defibrillator,and providing feedback to a rescuer performing the chest compressionsregarding rate of compression, depth of compression, or both.

In yet another implementation, there is disclosed a system for managingcare of a person receiving emergency cardiac assistance that comprisesone or more capacitors for delivering a defibrillating shock to apatient; one or more electronic ports for receiving signals from sensorsfor obtaining indications of an electrocardiogram (ECG) for the patient;and a patient treatment module executable on one or more computerprocessors to identify an phase in which a patient being monitored bythe system is in relative to a time at which an adverse cardiac eventfor patient began. The phase in which the patient being monitored by thesystem is in can includes an elapsed time since the adverse cardiacevent for the patient began, and a phase selected from an electrical,circulatory, and metabolic phase. The system may also comprise an outputmechanism arranged to indicate, to a user of the system, an indicationregarding the phase in which the patient is in. The output mechanism cancomprise a visual display, and the system can be programmed to displayto the user one indication of multiple possible indications, wherein theone indication indicates to the user the phase in which the patient isin.

In certain aspects, the system is programmed to display instructions forthe user to care for the patient, the instructions selected tocorrespond to the phase in which the patient is in. Also, the outputmechanism can include an interlock that prevents a user from deliveringa shock unless a determined likelihood of success of a shock revivingthe patient exceeds a determined value. In other aspects, the patienttreatment module comprises an ECG analyzer for generating an amplitudespectrum area (AMSA) value, an indication of heart rate for the patent,an indication of heart rate variability for the patent, or an indicationof ECG amplitude for the patent.

In yet other aspects, the indication of ECG amplitude comprises an RMSmeasurement, measured peak-to-peak, peak-to-trough, or an average ofpeak-to-peak or peak-to-trough over a specified interval. Also, thepatient treatment module can include an ECG analyzer for generating anindication of a first derivative of ECG amplitude for the patent, or anindication of a second derivative of ECG amplitude for the patent.Moreover, the patient treatment module can be programmed to determinewhether a defibrillation shock, prior to a future defibrillation shockbeing consider for delivery, was at least partially successful, andbased at least in part on the determination of whether the priordefibrillation shock was at least partially successful, modifying acalculation of a likelihood of success for delivering the futuredefibrillation shock.

In another implementation, a method for managing care of a personreceiving emergency cardiac assistance is disclosed and comprisesmonitoring, with an external defibrillator, electrocardiogram (ECG) datafrom a person receiving emergency cardiac assistance; performing amathematical transform f the ECG data from a time domain to a frequencydomain using a tapered window in the time domain; determining alikelihood of future defibrillation shock success using at least themathematical transformation; and affecting control of the externaldefibrillator based on the identification of whether a presentdefibrillation shock will likely be effective. The tapered window cancomprise a Tukey window, and can be between about one second and about 2seconds wide. The tapered window can be selected from a group consistingof Tukey, Hann, Blackman-Harris, and Flat Top, and the mathematicaltransform can comprise a Fast Fourier Transform.

In certain aspects, determining a likelihood of future defibrillationshock success comprises determining a value that is a function ofelectrocardiogram amplitude at particular different frequencies orfrequency ranges. It may also comprise determining an amplitude spectrumarea (AMSA) value for the ECG data. Also, determining a likelihood offuture defibrillation shock success can further comprise adjusting thedetermined AMSA value using information about a prior defibrillationshock. Moreover, the method can additionally include determining whetherthe adjusted AMSA value exceeds a predetermined threshold value. In someaspects, the method also includes providing to a rescuer a visual,audible, or tactile alert that a shockable situation exists for theperson receiving emergency cardiac assistance, if the adjusted AMSAvalue is determined to exceed the predetermined threshold value.

In yet other aspects, the method comprises determining whether a priordefibrillation shock was at least partially successful, and based atleast in part on the determination of whether the prior defibrillationwas at least partially successful, modifying a calculation of thelikelihood of success from delivering the future defibrillating shock.In certain aspects, determining a likelihood of success from deliveringa future defibrillating shock comprises performing a calculation by anoperation selected from a group consisting of logistic regression, tablelook-up, neural network, and fuzzy logic. The likelihood of success canalso be determined using at least one patient-dependent physicalparameter separate from a patient ECG reading, and the additionalpatient-dependent parameter can comprise an indication of trans-thoracicimpedance of the person receiving emergency cardiac care.

In additional aspects, the indication of trans-thoracic impedance isdetermined from signals sensed by a plurality of electrocardiogram leadsthat also provide the EGO data. The method can also comprise cyclicallyrepeating the actions of monitoring, determining, identifying andaffecting the control, and may also or alternatively include identifyingcompression depth of chest compressions performed on the personreceiving emergency cardiac assistance, using a device on the person'ssternum and in communication with the external defibrillator, andproviding feedback to a rescuer performing the chest compressions, thefeedback regarding rate of compression, depth of compression, or both.Also, the affecting control can include preventing a user fromdelivering a shock unless the determination of whether a shock will beeffective exceeds a determined likelihood level, and/or electronicallydisplaying, to a user, an indicator of the determined indication ofwhether a shock will be effective. In addition, displaying an indicatorcan include displaying a value, of multiple possible values in a range,that indicates a likelihood of success. Moreover, the calculation of thelikelihood of current shock success can be determined or modified usinga determination of a value of trans-thoracic impedance of the person.

Other features and advantages will be apparent from the description anddrawings, and from the claims.

DESCRIPTION OF DRAWINGS

FIG. 1A shows schematically the combination of various types of data inmaking a determination about likely effectiveness of a defibrillatingshock.

FIG. 1B shows a victim of a cardiac event being treated with a portabledefibrillator.

FIG. 1C is a graph that represents changes in AMSA during an eventcorrelated to phases in the event.

FIG. 1D is a table showing examples relating AMSA to predictedlikelihood of failure in defibrillating a victim who has or has not beenpreviously defibrillated.

FIG. 1E is a schematic diagram of a data structure for correlating AMSAand defibrillation success to predicted outcomes for shocking a victim.

FIG. 1F is a table showing predictions of successful defibrillation fordifferent AMSA threshold values in the instances of 1^(st)defibrillation attempts.

FIG. 1G is a table showing AMSA prior defibrillation for refractory andrecurrent VF.

FIG. 1H is a table showing prediction of successful defibrillation forincreasing AMSA threshold values in the instances of refractory VF.

FIG. 1I shows examples of window functions and resulting FFTs from thosefunctions.

FIG. 1J is a graph of area under curve for different windows.

FIG. 2 is a schematic block diagram that shows a defibrillator with anelectrode package and compression puck.

FIG. 3A is a flow chart of a process for providing a user with feedbackregarding a likelihood that a defibrillating shock will be successful.

FIG. 3B is a flow chart of a process for identifying a phase in acardiac event so as to provide guidance to a rescuer.

FIGS. 4A and 4B are graphs showing relationships between patient outcomeand AMSA threshold values for groups of patients having differenttrans-thoracic impedance values.

FIGS. 5A and 5B illustrate a defibrillator showing certain types ofinformation that can be displayed to a rescuer.

FIGS. 6A-6C show screenshots of a defibrillator display that providesfeedback concerning chest compressions performed on a victim.

FIGS. 7A and 7B show screenshots providing feedback regarding aperfusion index created from chest compressions.

FIGS. 8A and 8B show screenshots with gradiated scales indicating targetchest compression depths.

FIG. 9 shows a general computer system that can provide interactivitywith a user of a medical device, such as feedback to a user in theperformance of CPR.

DETAILED DESCRIPTION

In general, defibrillation is a common treatment for variousarrhythmias, such as VF. However, there can be undesired side effects(e.g., heart tissue damage, skin burns, etc.) that follow an electricalshock. Other undesired side effects of electric shock therapy includeunnecessary interruptions of chest compressions in the time required todeliver the shock. Added to this, the effectiveness of defibrillationcan fall generally over the elapsed time of an episode—where an episodemay be measured from the time when a victim first starts feelingsymptoms of cardiac arrest or loses consciousness and falls down.(Generally, the time from onset of a lethal VF episode andunconsciousness is relatively short, on the order of less than one-halfminute.) It is therefore desirable to predict whether defibrillationwill be successful in restoring a regular heartbeat following onset ofan arrhythmic episode, and/or to determine how long it has been since acardiac event started or what stage of the event the patient is in(e.g., a first, second, or third stage or phase).

Such predictions can each be referred to as an “indicator of success”or, equivalently, a “success indication” within the context of thepresent disclosure. The prediction may be used so that a defibrillatingshock is not provided when the chance of successful defibrillation islow, and instead a system will wait until the chance of successfuldefibrillation increases to an acceptable level, and until such a time,a rescuer can be instructed to provide other care such as regular chestcompressions, forceful chest compressions, or other care.

Such a determination about likelihood of successful shock can be used toalter care in an automatic and/or manual manner. In an automatic manner,a defibrillator may be made incapable of delivering a shock unless asuccess indication is above a determined level. In a manual manner, thesuccess indication may be shown to a rescuer, and the rescuer maydetermine whether to apply a shock or not based on the indication, orthe system may provide other information to the rescuer. For example,the indication of success may show a percentage likelihood that a shockwill succeed, or may be a less specific indicator, such as an indicationof which phase (e.g., of three phases discussed above and below) thevictim is currently in, so that the rescuer can immediately understand,from experience and training related to those phases, thatdefibrillation attempts are likely to be successful or not.

Additional information provided to a rescuer may take the form ofinstructions, such as instructions to perform chest compressions or someother action, where the action is selected from among a plurality ofpossible treatments based on the current phase for the victim. A systemmay also integrate both—e.g., locking out the ability to provide a shockuntil a threshold level is reached, and then showing the relativelikelihood of success above that value. The likelihood of success can beshown in various manners, such as by showing an actual percentage, orshowing two or more of a low, medium, or high likelihood of success,e.g., on an electronic display of a defibrillator.

In certain implementations described herein, the present disclosure isdirected to systems and methods for predicting whether defibrillationwill be effective using amplitude spectrum area (AMSA) or any otherappropriate Shock Prediction Algorithms (SPA) using analysis of ECGdata, and adjusting such SPA predictions based on either the existenceof prior defibrillation shocks as well as observations of a patient'sreaction to those defibrillating shocks. In particular, it has beenobserved that victims of cardiac fibrillation will successfullydefibrillate for lower AMSA threshold values if they have beenpreviously successfully defibrillated during the same rescue session.Thus, rather than treating each shock as a discrete event in analyzingthe probability of success, the techniques described here take intoaccount prior shock deliveries, and an observed response of the patientto those deliveries, in determining an AMSA value or other value thatwill indicate that a shock currently applied to the patient will likelybe successful (or not) in defibrillating the patient. Such adetermination may also be combined with determinations abouttrans-thoracic impedance (trans-thoracic impedance) of the patient, asdiscussed more fully below.

To obtain better predictive value for the AMSA values, the time windowfrom which the ECG data for an AMSA determination is taken may be maderelative small (e.g., between 3 and 4 seconds, between 2 and 3 seconds,and between 1 and 2 seconds), which will place the data as close to thecurrent status of the patient as possible. Smaller windows may sufferfrom edge effects more-so than larger windows, so the shape andcoefficients for the windows may also be selected to maximize predictivepower of the method. For example, a Tukey window having appropriatecoefficients, such as about 0.2, may be employed.

FIG. 1A shows schematically the combination 100 of various types of datain making a determination about likely effectiveness of a defibrillatingshock. In a particular implementation one of the types of data may beused alone, or multiple of the types may be combined so as to create acomposite likelihood—e.g., by giving a score to each type and a weight,and combining them all to generate a weighted composite score for alikelihood. In this example, a shock indication 116 is the outcome of adecision process that may be performed by a defibrillator alone or incombination with one or more pieces of ancillary equipment (e.g., acomputing device such as a smartphone carried by a healthcare provider).The shock indication 116 can be provided to part of the defibrillator,e.g., via an analog or digital signal that represents the indication, sothat the part of the defibrillator may cause a shock feature to beexecuted or to cause it to be enabled so that it can be manuallyexecuted by an operator of the defibrillator. The shock indication mayalso or alternatively be provided to the rescuer so as to indicate thatthe rescuer can or should cause a defibrillating shock to be delivered.(In the context of this disclosure, a defibrillating shock is one of alevel designed to cause defibrillation, but it does not need to besuccessful in causing the defibrillation.)

The relevant inputs may obtain at least some of their data from signalsgenerated by a pair of electrodes 102 that may be adhered to a patient'storso-above one breast and below the other, for example, in a typicalmanner. The electrodes may include leads for obtaining ECG data andproviding such data for analysis for a number of purposes. In addition,a CPR puck 104 may be placed on a patient's sternum and may deliversignals indicative of acceleration of the puck, and thus of up-downacceleration of the patient's sternum, which may be integrated so as toidentify a depth of compression by the rescuer (and can also be usedmore simply to identify whether the patient is currently receiving chestcompressions or not).

In certain implementations, the shape of the window may be asymmetric.For instance, the edge of the window that is “older” in time may have awindow shape that results in a greater level of attenuation that doesthe “newer” portion of the windowed data. Other assymetric shapes mayalso be used, as appropriate, to generate data that best represents anaccurate prediction of shock success.

The electrodes 102 may be electrically connected to an ECG unit 106,which may be part of a portable defibrillator and may combine data fromdifferent leads (e.g., 8 leads) in a familiar manner to construct asignal that is representative of the patient's ECG pattern. Such an ECGsignal is often used to generate a visual representation of thepatient's ECG pattern on a screen of the defibrillator. The ECG-relateddata may also be analyzed in various ways to learn about the currentcondition of the patient, including in determining what sort of shockindication to provide to control the defibrillator or to display to arescuer.

As one such example, ECG data may be provided to an AMSA analyzer 108,which may nearly continuously and repeatedly compute an AMSA number orsimilar indicator that represents ECG amplitude at particular differentfrequencies and/or frequency ranges in an aggregated form (e.g., anumeral that represents a value of the amplitude across thefrequencies). Generally, the goal is to identify a waveform in whichamplitude of the VF signals is large, and in particular, relativelylarge in the higher frequency ranges. Similarly, power spectrum area canbe measured and its value can be used as an input that is alternativeto, or in addition to, an AMSA value for purposes of making a shockindication. As described in more detail above and below, a current AMSAvalue (or a combination of multiple values over a short period) can beused to determine whether a shock is likely to be successful, and aplurality of combined AMSA values, such as a running average computedmany times over time (and each covering a time period longer than thetime period for the first AMSA value) using a moving window may indicatehow much time has elapsed since a cardiac event began and thus indicatewhich phase, of multiple phases during a VF event, the victim is in,where each phase calls for a different most-effective treatmentsub-protocol. Also, when rescuers first arrive on a scene, severalseconds of ECG data may be used to provide them an initial indication ofthe time since the event started and/or the phase in which the victimcurrently is in—e.g., by displaying a number of elapsed minutes or thename of one of multiple phases (like the three phases discussed above)on a display screen of a medical device such as a monitor ordefibrillator/monitor.

The AMSA analyzer 108 may be programmed to perform the analysis of theECG, and perhaps other, inputs so as to maximize the predictive value ofthe AMSA value, whether by affecting inputs to the AMSA determination,and/or making an AMSA determination and then adjusting the AMSA valuethat is generated from that determination. As one example, the size ofthe window from which ECG data is taken in making the calculation may beset to maximize the predictive value, such as by being about 1 second toabout 1.5 seconds long. As another example, the shape of the window maybe tapered, such as by being in the form of a Tukey or Hann window,rather than having vertical edges like a boxcar window. Similarly, thecoefficients for the window, such as Chi2 and p may be set to maximizethe expected predictive value of the calculation. The AMSA analyzer mayalso be programmed to change such values dynamically over the course ofa particular VF incident, either by moving the values progressively astime elapses so as to make the values match known expected values formaximizing the predictive effect of the calculation, or to respond toparticular readings, e.g., to use particular window length, form, orcoefficients when an AMSA value is in a certain defined range.

A trans-thoracic impedance module 110 may also obtain information fromsensors provided with the electrodes 102, which indicates the impedanceof the patient between the locations of the two electrodes. Theimpedance can also be a factor in determining a shock indication asdescribed in more detail below.

A defibrillation history success module 112 tracks the application ofdefibrillating shocks to the patient and whether they were successful indefibrillating the patient, and/or the level to which they weresuccessful. For example, the module 112 may monitor the ECG waveform intime windows of various sizes for a rhythm that matches a profile of a“normal” heart rhythm, and if the normal rhythm is determined to beestablished for a predetermined time period after the application of adefibrillating shock, the module 112 may register the existence of asuccessful shock. If a shock is applied and a normal rhythm is notestablished within a time window after the delivery of the shock, themodule 112 can register a failed shock. In addition to registering abinary value of success/fail, the module may further analyze the ECGsignal to determine the level of the success or failure and may, forexample, assign a score to the chance of success of each shock, such asa normalized score between 0 (no chance of success) and 1 (absolutecertainty).

A CPR chest compression module 114 may receive signals about the motionof the puck 104 to determine whether chest compressions are currentlybeing applied to the patient, and to determine the depth of suchcompressions. Such information may be used, for example, in giving arescuer feedback about the pace and depth of the chest compressions(e.g., the defibrillator could generate a voice that says “pushharder”). The presence of current chest compression activity may alsosignal the other components that a shock is not currently advisable, orthat ECG data should be analyzed in a particular manner so as to removeresidual artifacts in the ECG signal from the activity of the chestcompressions.

Information about pharmacological agents 115 provided to a patient mayalso be identified and taken into account in providing a shockindication to a rescuer. Such information may be obtained manually, suchas by a rescuer entering, via a screen on a defibrillator or on a tabletcomputer that communicates with the defibrillator, identifiers for thetype of agent administered to a patient, the time of administration, andthe amount administered. The information may also be obtainedautomatically, such as from instruments used to administer theparticular pharmacological agents. The device that provides a shockindication may also take that information into account in identifyingthe likelihood that a shock will be successful if provided to thepatient (e.g., by shifting up or down an AMSA threshold for measuringshock success likelihood), and for other relevant purposes.

One or more of the particular factors discussed here may then be fed toa shock indication module 116, which may combine them each according toan appropriate formula so as to generate a binary or analog shockindication. For example, any of the following appropriate steps may betaken: a score may be generated for each of the factors, the scores maynormalized (e.g., to a 0 to 1 or 0 to 100 scale), a weighting may beapplied to each of the scores to represent a determined relevance ofthat factor to the predictability of a shock outcome, the scores may betotaled or otherwise combined, and an indication can be determined suchas a go/no go indication, a percentage of likely success, and other suchindications.

In this manner then, the system 100 may take into account one or aplurality of factors in determining whether a shock to be delivered to apatient is likely to be successful. The factors may take data measuredfrom a plurality of different inputs (e.g., ECG, trans-thoracicimpedance, delivered agents, etc.), and may be combined to create alikelihood indication, such as a numerical score that is to be measuredagainst a predetermined scale (e.g., 0 to 100% likelihood or A to Fgrade). Such determination may then be used to control anautomatically-operated system (e.g., that delivers chest compressionsmechanically), to limit operation of a manually-operated system (e.g.,by enabling a shock that is triggered by a user pressing a button), orby simply providing information to a system whose shock is determinedsolely by a rescuer (e.g., for manual defibrillators in which theoperator is a well-trained professional).

FIG. 1B shows a victim 122 of cardiac arrest being cared for by arescuer and a defibrillator 124. The defibrillator 124 includes anelectrode package 126 and a compression puck 128 generally coupledthereto. An example of such a defibrillator includes the AED PLUSautomated external defibrillator or the AED PRO automated externaldefibrillator, both from ZOLL Medical Corporation of Chelmsford, Mass.Other embodiments of the defibrillator 124 are possible.

In the pictured example, the victim 122 is rendered prone due to anarrhythmic episode, and the electrode package 126 and the compressionpuck 128 are positioned on the torso of the victim 122 in an appropriateand known arrangement. In accordance with the present disclosure, thedefibrillator 124, in tandem with one or both of the electrode package126 and the compression puck 128, is configured to determine whether adefibrillation shock will be an effective measure to terminate thearrhythmic episode. The determination is generally based on priorsuccess or failure of defibrillating shocks, one or more trans-thoracicimpedance measurements, and one or more calculated AMSA values. As shownin the figure, the patient 122 is shown at two points in time—(a) pointt1 at which the patient has been defibrillated and is shown with hiseyes open and a healthy ECG pattern 135A to indicate such successfuldefibrillation, and (b) at a later time t2, when the patient hasrefibrillated and is shown with closed eyes to represent such a state,and with an erratic ECG trace 135B.

The defibrillator 124 is configured to acquire and manipulate both atrans-thoracic impedance signal 130 and an ECG signal 132 via theelectrode package. As described in further detail below, atrans-thoracic impedance measurement ( ) is a parameter derived from thetrans-thoracic impedance signal 130 that represents, among other things,thoracic fluid content. An AMSA value (V-Hz) is a parameter calculatedby integrating the Fourier transform of the ECG signal 132 over a finitefrequency range. The AMSA value is one form of calculation thatrepresents a value of an ECG signal from a victim, while other SPAvalues may likewise be computed.

The defibrillator 124 is further configured to display an indicator134A/B based on the defibrillating history (determined from ECG data),trans-thoracic impedance measurement(s) and AMSA value(s) obtained fromthe ECG signal 132, trans-thoracic impedance signal 130 and an ECGsignal 132, respectively. The indicator 134A/B generally provides aperceptible cue that suggests whether or not a particular defibrillationevent will likely terminate the arrhythmic episode of the victim 122.For example, for the victim 122 at time t1, the indicator 134A displaysan X to indicate that no shock should be delivered to the victim 122. Incontrast, at time t2, the indicator 1348 displays a success indicationof “88%,” so a rescuer (not shown) can be instructed “Press to Shock,”so as to apply a shock to the victim 122 via actuation of a control 136(e.g., a button that the user can actuate).

In this situation, the indication of an 88% likelihood of success wasmade by consulting data structure 130, which may be stored in memory ofdefibrillator 124 upon analysis that occurred around the time of t1, andapplying an appropriate calculation to data from the data structure 130.In particular, the defibrillator may analyze ECG data and an indicatorprovided by shock delivery circuitry in order to determine that a shockwas delivered, and at a time soon after, the patient's heart rhythmentered a normal pattern, such that the defibrillator 123 may determinethat the shock was a success at time t1. Upon making such adetermination, the defibrillator may update data structure 130 toindicate that a successful defibrillation event has occurred during therescue attempt. Other shocks may also be delivered, and the datastructure 130 may be updated to reflect such events, and the success orfailure of such events.

Data structure 130 or another data structure may also store informationabout prior AMSA readings for the victim during the particular VFepisode. For example, a separate AMSA measurement and calculation may bemade periodically (e.g., multiple times each second, once each second,or once every several seconds) and at least some past calculated AMSAvalues may be stored in data structure 130. Such values may be combined,and determinations may be made about general values (with lowvariability because of the combining) and trends in AMSA values, wheresuch determination may indicate information such as the progress of thevictim through phases that are generally indicative of the likelihood ofsuccess of particular actions taken on the victim by a rescuer.Moreover, such information may be used to generate an indication to arescuer of the elapsed time (approximate) since the victim entered VF,or an indication of the phase the victim is currently in, among otherthings.

Embodiments other than those that display a percentage likelihood for ashock indication are possible for the one likelihood indicationdiscussed here. For example, it will be appreciated that a successindication may be implemented as any appropriate type of perceptiblefeedback (e.g., haptic, audio, etc.) as desired. Two simultaneousindications may also be provided, where both may be the same style ofindication (e.g., visual display) or different types (e.g., visualdisplay for one and haptic for the other)—e.g., the phase in which avictim is currently located may be displayed on a screen of adefibrillator, while a current AMSA value indicating a relatively highchance of success may be communicated by vibration of or display on apuck on which the rescuer has placed his hands (so as to encourage therescuer to back-off and provide the shock).

In certain implementations, the defibrillator 124 may make thedetermination of a likelihood of success without expressly notifying therescuer, and may simply use the determination to determine when to tellthe rescuer that a shock may be delivered, or to provide otherinstructions to a rescuer. In other situations, the defibrillator 124may explicitly indicate the likelihood of success, such as by showing apercentage likelihood, by showing less discrete gradiations for success(e.g., poor, good, very good, and excellent), or by displaying a rangeof colors (e.g., with red indicating a poor chance and green indicatinga good chance). The type of indication that is displayed may also differbased on a mode in which the defibrillator 124 is operating—for example,in a professional mode, more detailed information may be provided,whereas in an AED mode, simpler information (a “go”/“no go” choice) maybe presented.

In such manner then, the defibrillator may conduct a number ofrelatively complex calculations and may combine multiple factors indetermining whether to allow a shock to be provided to a patient, or toencourage the application of such a shock by a rescuer.

FIG. 1C is a graph 130 that represents changes in AMSA during a VF eventcorrelated to phases in the event. In general, the graph 130 shows howAMSA varies along with variations in a patient ECG, and varies moregenerally over a longer time period by falling over time after the eventhas started.

The time across this graph may be, for example, about 15 minutes. Thetime is broken into three phases. A defibrillation phase 132 mayrepresent about the first 4 minutes (plus or minus one minute) of theevent. A deep CPR phase 134 may run from about four minutes to about 10minutes after onset of the event. And an Other CPR phase 136 mayrepresent the remainder of the event, assuming the victim has not beenrevived by that time.

Line 138 is represented as being drawn through all of the AMSA valuescomputed periodically throughout the time of the event. (The line isshown falling linearly here for clarity, though AMSA generally decreasesexponentially. If AMSA were graphed for a rescuer, it could be shown asan exponential curve, as a line on an exponential scale, and/or witherror bars showing statistical variation in the readings.) As can beseen, the AMSA values vary up and down (with a general downward trendover time), and such variation represents changes in the victim's ECGwhere the changes can represent changes in likelihood that a shock,currently delivered, will be successful. But although there isrelatively large variation over short time periods, the variation isless over longer time windows, such as over 10 or more seconds. Thus,for example, AMSA values may be computed periodically over a short timeperiod, and more general values may be computed by averaging orotherwise combining the individual measurements. A running average isrepresented by line 140. Line 140 may simply represent the average ofpast computations, and may also be extended into the future in certainimplementations, such as by linear regression or other appropriatestatistical techniques. For purposes of clarity, the overall AMSA valueis shown here as falling linearly with time, though the actual variationmay differ from what is shown here.

In this example, two points on line 140 are particularly relevant,points 142 and 144. These points represent locations at which thecombined AMSA value measurement (e.g., averaged over a window of time)fall below a predetermined value. For example, the value for point 142may have been selected from observations of ECG data, and correspondingAMSA values from data captured for actual real-world resuscitationevents with real victims, and such data may indicate that resuscitationfrom shock falls below an acceptable value and/or falls off more quicklyupon passing below a particular AMSA value. Such AMSA value may beselected as a cut-off point that defines the line between the firstphase and the second phase. Similarly, such data may indicate that chestcompressions or a particular type of chest compressions, such asforceful chest compressions, fell below a particular level ofeffectiveness or changed relatively rapidly in their effectiveness pastanother AMSA value. As such, point 144 may represent an AMSA valuedetermined from such data analysis to correspond to such changes asobserved across the large population of VF events. The points 142, 144are mapped to the determined values with horizontal dotted lines, and adefibrillator or other device may monitor the combined AMSA value as anevent progresses so as to identify when the predetermined AMSA value isreached. A similar monitoring may be employed with respect toidentifying the existence of point 144.

Each of the points 142, 144 is also mapped to the time axis,representing the time at which the particular victim was determined tohave transitioned from one phase to another. Generally, the times willbe relatively similar as between different victims and different cardiacevents, where the changes are driven in large part by ischemic effectsthat the event has on the heart tissue. At such points in time for theparticular victim represented by this graph, the behavior of a medicaldevice such as a defibrillator that is treating the victim may change inthe ways discussed above and below.

As such, the device may determine an estimated time since the VF eventbegan using AMSA values and/or other information, where particular AMSAvalues from a studied population have been determined to correspond tocertain times since collapse or other instantiation of the VF event.Such information may be displayed in real-time or stored, such as todetermine response times, and to perform studies on effectiveness ofrescuers as a function of the time since initiation of the event when adefibrillator is first connected and operable for the victim.

Example A

As for particular AMSA values for use in defining points 142 and 144,one example may be instructive. Data from an Utstein-compliant registryalong with electronic ECG records were collected on consecutive adultnon-traumatic OHCA patients treated by 2 EMS agencies over a 2 yearperiod. Patients with bystander witnessed CA and with VF as initial CArhythm were included (n=41). AMSA was calculated in earliest pausewithout compression artifacts, using a 2 second ECG with a Tukey (0.2)FFT window. VF duration was calculated as the sum of the time intervalfrom collapse to defibrillator on and the time interval fromdefibrillator on to first CPR interruption for defibrillation delivery.

VF duration ranged between 6.5 and 29.6 min (11.3+4.1 min), with acorresponding AMSA between 2.1 and 16.4 mV-Hz (9.4+4.2 mV-Hz). AMSAmeasured in the circulatory phase (N=19) was significantly higher thanthat in the metabolic phase (N=22) (8.14+3.17 vs. 5.98+2.88, p=0.03).Linear regression revealed that AMSA decreased in the analyzedpopulation by 0.22 mV-Hz for every min of VF. AMSA was able to predictcirculatory phase with an accuracy of 0.7 in ROC area. An AMSA thresholdof 10 mV-Hz was able to predict the circulatory phase with sensitivityof 32%, specificity of 95%, PPV of 86%, NPV of 62%, and overall accuracyof 66%.

FIG. 1D is a table showing examples that relate AMSA to predictedlikelihood of failure in defibrillating a victim who has or has not beenpreviously defibrillated. The data was generally analyzed to determinethe correlation between AMSA values and prior defibrillation success orfailure with respect to success of subsequent defibrillation attempts.

The table shows the results of analysis of 1291 quality defibrillationevents from 609 patients. AMSA was calculated for each such set of databased on a 1024 point ECG window that ended 0.5 seconds before eachdefibrillation. In the data, defibrillation was deemed successful when aspontaneous rhythm existed equal to or greater than 40 bpm and startingwithin 60 seconds from the shock, and also lasting for more than 30seconds. A range of AMSA thresholds was calculated and evaluated for thedata. The actual results shown in the other tables use the same orsimilar data.

In summary of the data, where no prior defibrillation had occurred, themean AMSA for successful shocks was 16.8 mV-HZ, while the mean forunsuccessful shocks was 11.4 (p<0.0001). For subsequent shocks, the meanAMSA value fell to 15.0 for successful shocks and 7.4 for unsuccessfulshocks.

Referring more specifically to the table itself, examples of data fromdefibrillation events were binned according to different AMSA valuesapplied to the data as AMSA thresholds that would be used to determinewhether to apply a subsequent shock. The first column of the table showsthe different assigned AMSA values, while the second column shows thenumber of events that the particular chosen AMSA value correctlypredicted, as compared to data indicating whether a defibrillation thatwas then applied was successful. The last column shows percentages withwhich the relevant AMSA value would have resulted in an accurateprediction if it had been used in the situations represented by the testdata.

The upper section shows statistics for a first defibrillation attemptfor each patient, while the lower section shows data for subsequentdefibrillation attempts. The data indicates that lower AMSA values mayprovide more accurate predictions for subsequent defibrillations thanfor earlier defibrillations.

The upper portion of the table shows a comparison of aggregate mean AMSAvalues of first versus second shock, second versus third shock, etc. Asthe data indicates, such AMSA values generally fall from the firstdefibrillation attempt to the second, and to a lesser amount generallyfor each additional defibrillation attempt.

FIG. 1E is a schematic diagram of a data structure for correlating AMSAand prior defibrillation shocks to predicted outcomes for shocking avictim. The data structure here is greatly simplified in an effort toshow how AMSA values and determinations about a number of prior shocks(successful or unsuccessful) may be used to predict whether anothershock will succeed. This particular table shows correlations for priorshocks generally, though additional tables may be needed for identifyingcorrelation for prior successful or unsuccessful shocks.

The table is shown in a format by which a program or human user couldenter at one side of the table to select the value of one inputvariable, and then move across to the value of another variable, andobtain for an output a percentage likelihood of success, For example,the number of prior shocks are listed across the x-axis at the top ofthe table, while the percentage likelihood of success is shown along theright edge on the y-axis. The values in the body of the table are AMSAvalues that have been normalized to a 0 to 100 scale. The actual valuesare not intended to represent any actual outcome or actual numbers, butsimply to indicate the interaction of the various values in coming to aconclusion about a likelihood of success.

Thus, for example, if a patient has received two defibrillating shocks,one would move to the third column of the table and then move down to ameasured AMSA number—say 60. One would then move to the right edge tosee the percentage likelihood of success—here, 70%. Values between thoseshown in the cells of the table can be rounded or interpolated orotherwise handled so as to provide likelihoods between each 10% valueshown in the data structure.

The likelihood of success identified from the data structure may then beused in various ways to implement the likelihood determination, such asproviding the number for the determined likelihood to a microprocessorthat can use it to determine whether to enable the shocking capabilityof a defibrillator and/or to display the value or a related value on thedefibrillator for review by a rescuer. Where additional factors (e.g.,trans-thoracic impedance) are to be considered, the table may take onadditional dimensions, multiple tables may be used, or other techniquesfor generating a likelihood that is a composite of multiple differentfactors may be used.

FIG. 1F is a table showing predictions of successful defibrillation fordifferent AMSA threshold values for instances of first defibrillationattempts. The threshold values are listed in the first column, and thecells to the right of each AMSA value indicate particular outcomes forshocks delivered at those AMSA values for initial shocks.

The particular values shown include sensitivity, specificity, positivepredictive value (PPV), negative predictive value (NPV), and accuracy,which are statistical measures of the performance of AMSA prediction forshock outcome. Sensitivity indicates the proportion of actual shocksuccesses that were correctly identified. For example, if there were 100shock successes, and 60 of the 100 were identified by an AMSA thresholdof 10 mVHz, then the sensitivity is 0.6 using 10 mVHz as the AMSAthreshold. Specificity represents the proportion of shock failures thatwere correctly identified by the particular AMSA value. PPV is the shocksuccess rate. For example, if 10 mVHz was used as the AMSA threshold todeliver shocks and 100 shocks were delivered with 60 defibrillationsuccesses, PPV=0.6. NPV is the shock failure rate. For example, if 10mVHz was used as the AMSA threshold for the 100 cases, with AMSA<10failing to shock, there are 90 cases of failed shock, or NPV=0.9.Accuracy is the proportion of true results (correctly predicted as shocksuccess and shock failure by AMSA) in the total patient population.

FIG. 1G is a table showing AMSA prior defibrillation for refractory andrecurrent VF. In particular, the table shows AMSA values that weremeasured before a defibrillating shock was delivered, and thencorrelated to whether the shock was successful or not. The first rowshows the mean AMSA for all shocks, successful or unsuccessful, brokenout by whether refractory VF was present or recurrent VF was present(where mean+/−SEM is shown for each of the values in the table). Thesecond row shows the AMSA, for both refractory and recurrent VF, wherethe result of the shock was a successful defibrillation, while the thirdrow shows corresponding values for shocks that did not successfullydefibrillate. The final row shows the shocks that were successful indefibrillating the subject, both in terms of percentage and numbers. Ascan be seen, the level of success was much higher for recurrent VF thanfor refractory VF, and the AMSA was also higher.

FIG. 1H is a table showing prediction of successful defibrillation forincreasing AMSA threshold values in the instances of refractory VF. Theparameters shown in the table are similar to those shown for FIG. 1E.

FIG. 1I shows examples of window functions and resulting FFTs from thosefunctions. As noted above, window widths in the time domain of less than4 second down to about one second, less than three seconds down to aboutone second, and less than two seconds down to about one second, may beused. The figure shows, at the top, a boxcar window that is not taperedand thus may have negative transitory effects introduced into the FFTthat it produces. The figure shows, at the bottom, a Tukey window, whichis tapered as a sine wave, and is capped at a maximum value beforecoming down on the back side according to the falling value for the sinewave. The window thus lessens the effect of transients cause by thesudden switching of the boxcar window.

FIG. 1J shows ROC (receiver operating characteristic) Area values forfive different window functions applied to a one second window of ECGdata. In this example, digitalized ECG recordings were collected frommultiple emergency medical services in the U.S. through a regular fieldcase submission program. The sampling rate of all the ECG data files was250 Hz. An episode of 1.025 seconds (256 data points, sample rate 250Hz) waveform ending at 0.5 seconds before each shock attempt wereselected for analysis. Five windowing functions were used for analysis.Shock success was defined as an organized rhythm that was present for aminimum of 30 seconds, starting within 60 seconds after the shock, andthat had a rate of 40 beats per minute or greater.

Certain values shown in the figure have diagnostic value when used incombination with the methods discussed here. For example, When comparingone method of analysis to another, a “p-value” provides a measure of adifference between two groups of measurements, with lower p-valuesgenerally being better compared to higher p-values. By statisticalconvention, a value of p<0.05 is considered to be statisticallysignificant. An Area Under the Curve (“AUC”) measures the area under theROC curve. The “squarer” the ROC curve is, the greater the accuracy ofthe diagnostic in general; the AUC is greater for “squarer” curves. TheChi-square test is a simple statistical comparison of the probabilitydistribution of two or more groups where the outcomes are binary.

A total of 1291 shocks (321 successful) from 609 patients with witnessedVF were included in the analysis. As shown in FIG. 1J, a Tukey window(R=0.2) resulted in significantly higher area under the ROC curvecompared to other FFT windows.

Thus, as shown by this study, a defibrillator or other device asdiscussed above and below may be programmed to make AMSA determinationsfor purposes of predicting a likelihood of successful defibrillatingshock using a Tukey window of a width of about 1 second. In otherinstances, it may be determined that one of the other three types oftapered windows is appropriate, or at least more appropriate than thenon-tapered rectangular, or boxcar, window function. Similarly, multipledifferent window functions may be used for a particular patient, and anAMSA value may be generated from a combination of the different windowfunction readings.

Each of these tables represent values that may be provided as parametersfor the operation of a device that determines likelihood of success fora shock or provides other determinations for use in providing care to apatient suffering from VF. For example, the values determined fromtesting a large number of past events may be used as values thatdetermine the likelihood values that a device correlates with aparticular AMSA value at a particular time after VF starts. In thismanner, then, data from observations of care provided to prior patientsmay be used to program a system for providing better case to futurepatients, particularly with respect to providing guidance on when ashock is likely to be successful in defibrillating the patient.

Referring now to FIG. 2, a schematic block diagram 200 shows an exampledefibrillator 201, along with the example electrode package 102 andcompression puck 104, of FIG. 1A in more detail. In general, thedefibrillator 201, and optionally one or more of the electrode package102 and compression puck 104, defines an apparatus for administeringcare to a patient, subject, or individual (e.g., victim 102) whorequires cardiac assistance.

The defibrillator 201 includes a switch 202 and at least one capacitor204 for selectively supplying or applying a shock to a subject. Thedefibrillator 201 further includes an ECG analyzer module 206, atrans-thoracic impedance module 208, a CPR feedback module 210 thatcontrols frequency and magnitude of chest compressions applied to asubject, a patient treatment (PT) module 212 (which includes adefibrillation history analyzer 215), a speaker 214, and a display 216.In this example, the ECG analyzer module 206, trans-thoracic impedancemodule 208, CPR feedback module 210, and patient treatment (PT) module212 are grouped together as a logical module 218, which may beimplemented by one or more computer processors. For example, respectiveelements of the logical module 218 can be implemented as: (i) a sequenceof computer implemented instructions executing on at least one computerprocessor of the defibrillator 201; and (ii) interconnected logic orhardware modules within the defibrillator 201, as described in furtherdetail below in connection with FIG. 6.

In the example of FIG. 2, the electrode package 102 is connected to theswitch 202 via port on the defibrillator 201 so that different packagesmay be connected at different times. The electrode package 102 may alsobe connected through the port to ECG analyzer module 206, andtrans-thoracic impedance module 208.

The compression puck 104 is connected, in this example, to the CPRfeedback module 210. In one embodiment, the ECG analyzer module 206 is acomponent that receives an ECG (e.g., ECG signal 112). Similarly, thetrans-thoracic impedance module 208 is a component that receivestransthoracic impedance (e.g., trans-thoracic impedance signal 110).Other embodiments are also possible.

The patient treatment module 212 is configured to receive an input fromeach one of the ECG analyzer module 206, trans-thoracic impedance module208, and CPR feedback module 210. The patient treatment module 212 usesinputs as received from at least the ECG analyzer module 206 andtrans-thoracic impedance module 208 to predict whether a defibrillationevent will likely terminate an arrhythmic episode. For example, ECG datacan be used both to determine AMSA values for a patient, and alsodetermine whether shocks are effective or not so that such informationcan be saved and used to identify likelihoods that subsequent shockswill be effective). In this manner, the patient treatment module 212uses information derived from both an ECG signal (both for AMSA and foradjusting the AMSA value) and transthoracic impedance measurement toprovide a determination of a likelihood of success for delivering adefibrillating shock to a subject.

The patient treatment module 212 is further configured to provide aninput to each one of the speaker 214, display 216, and switch 202. Ingeneral, input provided to the speaker 214 and a display 216 correspondsto either a success indication or a failure indication regarding thelikelihood of success for delivering a shock to the subject. In oneembodiment, the difference between a success indication and a failureindication is binary and based on a threshold. For example, a successindication may be relayed to the display 216 when the chancescorresponding to a successful defibrillation event is greater than 75%.In this example, the value “75%” may be rendered on the display 216indicating a positive likelihood of success. When a positive likelihoodof success is indicated, the patient treatment module 212 enables theswitch 202 such that a shock may be delivered to a subject.

The patient treatment module 212 may also implement an ECG analyzer forgenerating an indication of heart rate for the patent, for generating anindication of heart rate variability for the patent, an indication ofECG amplitude for the patent, and/or an indication of a first or secondderivative of ECG amplitude for the patient. The indication of ECGamplitude can include an RMS measurement, measured peak-to-peak,peak-to-trough, or an average of peak-to-peak or peak-to-trough over aspecified interval. Such indications obtained by the ECG analyzer may beprovided to compute an AMSA value for the patient and/or can be used incombination with a computed AMSA value so as to generate some derivativeindication regarding whether a subsequent shock is likely or unlikely tobe effective (and the degree, e.g., along a percentage scale, of thelikelihood).

In another embodiment, likelihood of a successful defibrillation eventmay be classified into one of many possible groups such as, for example,low, medium, and high likelihood of success. With a “low” likelihood ofsuccess (e.g., corresponding to a successful defibrillation event isless than 50%), the patient treatment module 212 disables the switch 202such that a shock cannot be delivered to a subject. With a “medium”likelihood of success (e.g., corresponding to a successfuldefibrillation event is greater than 50% but less than 75%), the patienttreatment module 212 enables the switch 202 such that a shock may bedelivered to a subject, but also renders a warning on the display 216that the likelihood of success is questionable. With a “high” likelihoodof success (e.g., corresponding to a successful defibrillation event isgreater than or equal to 75%), the patient treatment module 212 enablesthe switch 202 such that a shock may be delivered to a subject, and alsorenders a cue on the display 216 indicating that the likelihood ofsuccess is very good. Still other embodiments are possible.

Thus, the system 200 may provide, in a portable electric device (e.g., abattery-operated device) the capability to analyze a number of inputsand to identify a variety of factors from those inputs, where thefactors can then be combined to provide a flexible, intelligentdetermination of likely success. Referring now to FIG. 3A, an examplemethod 300 is shown for administering care to an individual requiringcardiac assistance. In one embodiment, the method 300 is implemented bythe example defibrillators described above in connection with FIGS. 1Band 2. However, other embodiments are possible.

At a step 302, at least one of an ECG signal (e.g., ECG signal 112) anda trans-thoracic impedance signal (e.g., trans-thoracic impedance signal110) of the subject receiving cardiac care is monitored. In general, anindividual receiving cardiac care includes the individual at any timeduring a cardiac event, including whether or not individual is receivingactive care (e.g., chest compressions).

At a step 304, a trans-thoracic impedance value is extracted from thetrans-thoracic impedance signal as monitored at step 302. Additionally,at step 304, an AMSA value can be calculated from the ECG signal asmonitored at step 302 by integrating the Fourier transform (e.g., FFT)of the ECG signal over a finite frequency range. Example frequencycontent of an arrhythmic ECG signal generally ranges between about 1 Hzto about 40 Hz, with amplitude of about 50 mV or less. An example of anAMSA value calculated from such a signal ranges between about 5 mV-Hz toabout 20 mV-Hz. It will be appreciated however that this is only anexample, and that the magnitude and spectra of an ECG signal rangesgreatly.

The AMSA value may be determined from a moving window that moves in timethrough the incoming ECG data as it arrives (e.g., the raw ECG data maybe cached for a period at least as long as the window), where the windowmay be about one second wide (or more), and can be measured multipletimes each second so that there are overlapping windows. The window mayalso have a tapered (rather than rectangular) window function so as toimprove the accuracy of the AMSA value in predicting defibrillationsuccess. Furthermore, the coefficients for the window may be selected tomaximize the predictive ability of the system. In addition, multipledifferent AMSA values may be determined (e.g., with different windowsize, type, and/or coefficients) and a most-accurate AMSA may bedetermined and used to make a prediction, or a composite value may begenerated from each of the determined AMSA values.

Additionally, the window size, type, and coefficients can change overtime to allow a system to dynamically adjust to a particular VF event.For example, using determinations about the phase in which a VF eventis, a system may change such parameters to switch to a window that isdetermined to better predict defibrillation success. Alternatively, ablend of window techniques may be used and the blend may change overtime, while a composite prediction score is determined from the blendedtechniques.

For example, a system could shift from a symmetric window to anasymetrric window just prior to the end of a CPR interval as it getscloser to the time of a shock. The system may be continuously executinga noise detection process, and if sections of the data in the window arefound to have ECG with anomalously high amounts of higher frequencynoise compared to ECG in adjacent sections, then those portions of thewindow can be attenuated via adjusting the window characteristics. Ifthe burst of noise occurs in the middle of the window, then the windowfunction can be composed of two adjacent Tukey or other windows wherethe null of the superimposed windows is centered at the occurrence ofthe noise burst. Thus, various dynamic changes may be made to the windowas the process occurs so as to adjust to particular activities for apatient.

At a step 306, the process identifies success levels of prior shocksapplied to the patient during the cardiac event. Such determination mayoccur in various manners. At a simplest level, the process may simplytrack the number of times a defibrillating shock has been provided tothe patient. In more complex implementations, the process may identifyhow many attempts were successful and how many were not, and in aslightly more complex implementation, may identify which were successfuland which were not (e.g., because subsequent steps may perform moreaccurately by weighting the influence of different ones of the priordefibrillations in different ways). In yet more complex systems, thedegrees of prior success can be determined, which may includedetermining how close the patient's defibrillated heart rate was to apredetermined rate (either a particular rate or a range of rates) or howconsistent the rate was over time, or a combination of both to generatea score for the quality of the defibrillation. Other examples ofphysiologic measure that may be useful for generating a score may bepulse oximetry, capnography, blood pressure, or other pulse or bloodflow detection methods.

As one such example, scoring the ECG quality of the post-shock ECGrhythm may occur by giving heart rates in the range of 50-90 BPM ahigher score than those above or below that range (with the scoredecreasing the further from that range the heart rates were). Morecomplex scoring systems could additionally or alternatively be used,such as using a windowing function that weights a heart rate of apatient to generate a normalized score. Such a windowing functions mightbe a Hamming window or a Tukey window with a rectangle width that isflat from 50-90 BPM. In each such situation, the data gathered for eachdefibrillation may be saved so that it can be accessed in preparationfor determining and providing identifications of likely success forlater defibrillations.

At step 308, the process determines a combined indicator of success thatincludes an indication from trans-thoracic impedance and an indicationfrom an ECG reading, such as an AMSA indication, and is modifiedappropriately to reflect data about prior successes or failure indefibrillation. The combined indicator may be determined by inputting atrans-thoracic impedance value, an AMSA value, and a count or otherindicator of prior success or failure, into a function or look-up table,or may be determined without a need to compute both or all values first,such as by taking inputs indicative of all values and computing apredictor of success directly from such indicative values. Alternativelyto using a table to calculate the predictive score, the use of logisticregression may be used with a logistic regression equation, with inputsto the equation with, e.g. ECG rhythm type, ECG rate, transthoracicimpedance, prior shocks, etc. Neural network or fuzzy logic methods orother non-linear decision-making methods may also be used. In certaininstances, a single value, like AMSA may be used to compute thelikelihood of success.

At box 310, a success indication is provided to a defibrillatoroperator. The indication may take a variety of forms. For example, theability of the defibrillator to deliver a shock may be enabled when theindicator of success is higher than a threshold level, so that thesuccess indicator is delivered by the operator being shown that a shockcan or cannot be delivered. Also, the operator may be notified that thedefibrillator can provide a shock, and may be prompted to push aphysical button to cause the shock to be delivered.

In some implementations, the operator may also be provided with moredetail about the success indication. For example, the operator may beshown a percentage number that indicates a likelihood in percent thatthe shock will be successful. Alternatively, or in addition, theoperator may be shown a less granular level of an indication, such as avalue of “excellent,” “good,” and “poor” to indicate to the operatorwhat the likelihood of successful defibrillation is.

At box 312, the trigger mechanism is enabled on the defibrillator, asdiscussed above. In certain instances, such a feature may be enabledwhenever a shockable rhythm is observed for a patient. In othercircumstances, the enabling may occur only when the combined indicationdiscussed above exceeds a threshold value for indicating that a shockwill be successful in defibrillating the patient. For a hybriddefibrillator that is capable of manual and AED modes, the triggermechanism may operate different depending on what mode the defibrillatoris in.

An arrow is shown returning to the top of the process to indicate thatthe process here is in ways continuous and in ways repeated. Inparticular, ECG signals are gathered continuously, as are other types ofdata. And the process repeatedly tries to identify whether a shock canor should be provided, and the order and timing of the steps in thatcycling may be dictated by standards as adjusted by a medical directoror other appropriate individual responsible for the deployeddefibrillator. Thus, for instance, the entire process may be repeated,certain portions may be repeated more frequently than others, andcertain portions may be performed once, while others are repeated.

FIG. 3B is a flow chart of a process 320 for identifying a phase in acardiac event so as to provide guidance to a rescuer. In general, theprocess involves using AMSA or other determinations to identify a lengthof time since a cardiac event has begun and/or a phase in which theevent is currently located, where different phases are delineated by therelative likelihood of certain treatment approaches operatingsuccessfully vis-à-vis other phases.

The process 320 in this example begins at box 322, where a patient ismonitored generally, such as by monitoring the patient's pulse and ECG,among other things. Such monitoring may be the same monitoring as instep 302 in FIG. 3A or may occur concurrently with such monitoring. Themonitoring may constitute constantly receiving ECG data and periodicallycomputing (e.g., every second or every two seconds) AMSA and othervalues from it. At the same time, an ECG representation may be displayedto an operator of a defibrillator or other medical device.

At box 324, the AMSA is determined, and may be calculated in knownmanners from the ECG data. Other SPAs may also be operated on theincoming data from the patient. As discussed above, the AMSA value maydepend on a window function of a certain determined length and type, andhaving certain determined coefficients, where each of these parametersmay be adjusted dynamically over the time of a VF incident.

At box 326, prior AMSA measurements are identified. Such a step mayoccur simply by looking to a known location in memory where a softwareprogram has been programmed to store such information. Thosemeasurements or computations may be loaded to a location at which theycan be manipulated relative to each other, including by combining thoseseparate measurements into a composite, such as an average of themeasurements. In obtaining such measurements, the process may fetch onlyn number of prior measurements with each cycle of the process, so that arolling or sliding average is computed at each step. The number ofvalues to combine in any given cycle can be selected so as to providesufficient responsiveness (fewer readings) while providing a sufficientgeneral view of the status of the patient that is not subject to extremefluctuations (more readings).

At box 328, the current general AMSA level (e.g., from an average ofmultiple prior readings) is determined. Other measures of a similar typemay also or alternatively be generated, if they represent theprogression of the patient through nonrecurring phases of a cardiacevent, such as those discussed above.

At box 330, the phase in the progression of the VF event is determinedfor the patient. Such a determination may include simply estimating,with the AMSA level or other such data, the time since the patiententered cardiac arrest, and/or more generally whether the patient is inelectrical, circulatory, or metabolic phase. For example, the AMSA levelfor the patient may be provided to a look-up table that maps observedAMSA values for a population to event phases or time since the eventstarted, or both.

At box 332, the process provides an indication of care that iscorrelated to the phase of the event. For example, a screen on adefibrillator may show a message indicating that the rescuer shouldprepare to administer a shock (e.g., if the patient is in electricalphase and the AMSA determination shows a high likelihood that the shockwill be successful). Similarly, color may be used to show one or more ofthe parameters, such as a single color bar to show likelihood of shocksuccess, where the likelihood is based on current AMSA, combined AMSAvalues (e.g., an average or trend), or a combination of both.

FIG. 4A shows a plot of positive predictive value (%) versus AMSAthreshold (mv-Hz) for a first set of subjects having a trans-thoracicimpedance measured greater than 150 ohms and a second set of subjectshaving a trans-thoracic impedance measured less than 150 ohms. As shownby the comparative data, the first set of subjects generally has agreater positive predictive value for a given AMSA threshold. In bothcases, positive predictive value generally increases with increasingAMSA threshold. Thus, an indication of success for a patient having alow impedance may be provided when the AMSA value is lower, than for acomparable AMSA value from a high impedance patient. Or, where apercentage likelihood of success is shown, the displayed percentage fora particular AMSA value may be higher for a low impedance patient ascompared to a high impedance patient—at least with the range of AMSAvalues from 5-20 my-HZ.

FIG. 4B shows a plot of sensitivity (unit-less) versus AMSA threshold(mv-Hz) for a first set of subjects having a trans-thoracic impedancemeasured less than 100 ohms, a second set of subjects having atrans-thoracic impedance measured between 125 ohms and 150 ohms, and athird set of subjects having a trans-thoracic impedance measured between150 ohms and 180 ohms. As shown by the comparative data, AMSA thresholdgenerally increases, for a given specificity, with increasingtrans-thoracic impedance.

FIG. 5A shows a defibrillator showing certain types of information thatcan be displayed to a rescuer. In the figure, a defibrillation device500 with a display portion 502 provides information about patient statusand CPR administration quality during the use of the defibrillatordevice. As shown on display 502, during the administration of chestcompressions, the device 500 displays information about the chestcompressions in box 514 on the same display as is displayed a filteredECG waveform 510 and a CO2 waveform 512 (alternatively, an SpO2 waveformcan be displayed).

During chest compressions, the ECG waveform is generated by gatheringECG data points and accelerometer readings, and filtering themotion-induced (e.g., CPR-induced) noise out of the ECG waveform.Measurement of velocity or acceleration of chest compression duringchest compressions can be performed according to the techniques taughtby U.S. Pat. No. 7,220,335, titled Method and Apparatus for Enhancementof Chest Compressions During Chest Compressions, the contents of whichare hereby incorporated by reference in their entirety.

Displaying the filtered ECG waveform helps a rescuer reduceinterruptions in CPR because the displayed waveform is easier for therescuer to decipher. If the ECG waveform is not filtered, artifacts frommanual chest compressions can make it difficult to discern the presenceof an organized heart rhythm unless compressions are halted. Filteringout these artifacts can allow rescuers to view the underlying rhythmwithout stopping chest compressions.

The CPR information in box 514 is automatically displayed whencompressions are detected by a defibrillator. The information about thechest compressions that is displayed in box 514 includes rate 518 (e.g.,number of compressions per minute) and depth 516 (e.g., depth ofcompressions in inches or millimeters). The rate and depth ofcompressions can be determined by analyzing accelerometer readings.Displaying the actual rate and depth data (in addition to, or insteadof, an indication of whether the values are within or outside of anacceptable range) can also provide useful feedback to the rescuer. Forexample, if an acceptable range for chest compression depth is 1.5 to 2inches, providing the rescuer with an indication that his/hercompressions are only 0.5 inches can allow the rescuer to determine howto correctly modify his/her administration of the chest compressions(e.g., he or she can know how much to increase effort, and not merelythat effort should be increased some unknown amount).

The information about the chest compressions that is displayed in box514 also includes a perfusion performance indicator (PPI) 520. The PPI520 is a shape (e.g., a diamond) with the amount of fill that is in theshape differing over time to provide feedback about both the rate anddepth of the compressions. When CPR is being performed adequately, forexample, at a rate of about 100 compressions per minute (CPM) with thedepth of each compression greater than 1.5 inches, the entire indicatorwill be filled. As the rate and/or depth decreases below acceptablelimits, the amount of fill lessens. The PPI 520 provides a visualindication of the quality of the CPR such that the rescuer can aim tokeep the PPI 520 completely filled.

As shown in display 500, the filtered ECG waveform 510 is a full-lengthwaveform that fills the entire span of the display device, while thesecond waveform (e.g., the CO2 waveform 512) is a partial-lengthwaveform and fills only a portion of the display. A portion of thedisplay beside the second waveform provides the CPR information in box514. For example, the display splits the horizontal area for the secondwaveform in half, displaying waveform 512 on left, and CPR informationon the right in box 514.

The data displayed to the rescuer can change based on the actions of therescuer. For example, the data displayed can change based on whether therescuer is currently administering CPR chest compressions to thepatient. Additionally, the ECG data displayed to the user can changebased on the detection of CPR chest compressions. For example, anadaptive filter can automatically turn ON or OFF based on detection ofwhether CPR is currently being performed. When the filter is on (duringchest compressions), the filtered ECG data is displayed and when thefilter is off (during periods when chest compressions are not beingadministered), unfiltered ECG data is displayed. An indication ofwhether the filtered or unfiltered ECG data is displayed can be includedwith the waveform.

Also shown on the display is a reminder 521 regarding “release” inperforming chest compression. Specifically, a fatigued rescuer may beginleaning forward on the chest of a victim and not release pressure on thesternum of the victim at the top of each compression. This can reducethe perfusion and circulation accomplished by the chest compressions.The reminder 521 can be displayed when the system recognizes thatrelease is not being achieved (e.g., signals from an accelerometer showan “end” to the compression cycle that is flat and thus indicates thatthe rescuer is staying on the sternum to an unnecessary degree). Such areminder can be coordinated with other feedback as well, and can bepresented in an appropriate manner to get the rescuer's attention. Thevisual indication may be accompanied by additional visual feedback nearthe rescuer's hands, and by a spoken or tonal audible feedback,including a sound that differs sufficiently from other audible feedbackso that the rescuer will understand that release (or more specifically,lack of release) is the target of the feedback.

FIG. 5B shows the same defibrillator, but with an indicator box 522 nowshown across the bottom half of the display and over the top ofinformation that was previously displayed to display a successindication of “75%.” Similar to the display 216 as described above, theindicator box 522 can generally convey a success indication or a failureindication regarding the likelihood of success for delivering a shock toa subject. The success indication can be generated using any combinationof the techniques discussed above, including AMSA values, measures ofprior effectiveness or ineffectiveness of prior defibrillating shocks,and trans-thoracic impedance.

In certain instances, one or more of the inputs used for determining alikelihood that a future shock will be successful, will not beavailable. For example, at times it may not be possible to calculateAMSA accurately when CPR compressions are occurring. Or perhaps a systemis receiving values for trans-thoracic impedance that are not possible,which would indicate a problem with the sensors measuring such impedanceor other similar problems. In such situations, the score that isgenerated to indicate a likelihood of success may be switched to a scorethat depends only on n−1 inputs (where n is the optimal number ofinputs, and n−1 represents the removal of one of the inputs). Thus, thesystem may be adaptive to problems with particular ones of the inputsthat indicate a likelihood of success, yet the system may stilldetermine a likelihood of success that is as accurate as possible giventhe inputs that are available.

In the example shown, the success indication is textual; however thesuccess indication (and/or failure indication) can generally beimplemented as any type of perceptible feedback. For example, tone,color, and/or other perceptible visual effects can be rendered orotherwise displayed to a user via the indicator box. For example, thecharacters “75%” may be highlighted or otherwise distinguished in a boldcolor, and the phrase “Press to Shock” may blink at least intermittentlyto convey a sense of urgency with respect to a pending shock. Otherembodiments are possible.

FIGS. 6A-6C show example screens that may be displayed to a rescuer on adefibrillator. Each of the displays may be supplemented with anindicator-like box 522 in FIG. 5B when the defibrillator makes adetermination as to the likelihood of success for delivering a shock toa subject.

FIG. 6A shows exemplary information displayed during the administrationof CPR chest compressions, while FIGS. 6B and 6C show exemplaryinformation displayed when CPR chest compressions are not being sensedby the defibrillator. The defibrillator automatically switches theinformation presented based on whether chest compressions are detected.An exemplary modification of the information presented on the displaycan include automatically switching one or more waveforms that thedefibrillator displays. In one example, the type of measurementdisplayed can be modified based on the presence or absence of chestcompressions. For example, CO2 or depth of chest compressions may bedisplayed (e.g., a CO2 waveform 620 is displayed in FIG. 6A) during CPRadministration, and upon detection of the cessation of chestcompressions, the waveform can be switched to display an SpO2 or pulsewaveform (e.g., an SpO2 waveform 622 is displayed in FIG. 6B).

Another exemplary modification of the information presented on thedisplay can include automatically adding/removing the CPR informationfrom the display upon detection of the presence or absence of chestcompressions. As shown in FIG. 6A, when chest compressions are detected,a portion 624 of the display includes information about the CPR such asdepth 626, rate 628, and PPI 630. As shown in FIG. 6B, when CPR ishalted and the system detects the absence of CPR chest compressions, thedefibrillator changes the CPR information in the portion 624 of thedisplay, to include an indication 632 that the rescuer should resumeCPR, and an indication 634 of the idle time since chest compressionswere last detected. In a similar manner, when the defibrillatordetermines that rescuers should change, the label 632 can change to amessage such as “Change Who is Administering CPR.” In other examples, asshown in FIG. 6C, when CPR is halted, the defibrillation device canremove the portion of the display 624 previously showing CPR data andcan display a full view of the second waveform. Additionally,information about the idle time 636 can be presented on another portionof the display.

FIGS. 7A and 7B show defibrillator displays that indicate to a rescuerlevels of perfusion being obtained by chest compressions that therescuer is performing. FIG. 7A shows exemplary data displayed during theadministration of CPR chest compressions when the CPR quality is withinacceptable ranges, while FIG. 7B shows modifications to the display whenthe CPR quality is outside of the acceptable range.

In the example shown in FIG. 7B, the rate of chest compressions hasdropped from 154 compressions per minute (FIG. 7A) to 88 compressionsper minute. The defibrillator device determines that the compressionrate of 88 compressions per minute is below the acceptable range ofgreater than 100 compressions per minute. In order to alert the userthat the compression rate has fallen below the acceptable range, thedefibrillator device provides a visual indication 718 to emphasize therate information. In this example, the visual indication 718 is ahighlighting of the rate information. Similar visual indications can beprovided based on depth measurements when the depth of the compressionsis shallower or deeper than an acceptable range of depths. Also, whenthe change in rate or depth indicates that a rescuer is becomingfatigued, the system may display a message to switch who is performingthe chest compressions, and may also emit aural or haptic feedback tothe same effect.

In the examples shown in FIGS. 7A and 7B, a perfusion performanceindicator (PPI) 716 provides additional information about the quality ofchest compressions during CPR. The PPI 716 includes a shape (e.g., adiamond) with the amount of fill in the shape differing based on themeasured rate and depth of the compressions. In FIG. 7A, the depth andrate fall within the acceptable ranges (e.g., at least 100compressions/minute (CPM) and the depth of each compression is greaterthan 1.5 inches) so the PPI indicator 716 a shows a fully filled shape.In contrast, in FIG. 7B, when the rate has fallen below the acceptablerange, the amount of fill in the indicator 716 b is lessened such thatonly a portion of the indicator is filled. The partially filled PPI 716b provides a visual indication of the quality of the CPR is below anacceptable range.

As noted above with respect to FIG. 5A, in addition to measuringinformation about the rate and depth of CPR chest compressions, in someexamples the defibrillator provides information about whether therescuer is fully releasing his/her hands at the end of a chestcompression. For example, as a rescuer tires, the rescuer may beginleaning on the victim between chest compressions such that the chestcavity is not able to fully expand at the end of a compression. If therescuer does not fully release between chest compressions the quality ofthe CPR can diminish. As such, providing a visual or audio indication tothe user when the user does not fully release can be beneficial. Inaddition, such factors may be included in a determination of whether therescuer's performance has deteriorated to a level that the rescuershould be instructed to permit someone else perform the chestcompressions, and such information may be conveyed in the variousmanners discussed above.

As shown in FIG. 8A, a visual representation of CPR quality can includean indicator of CPR compression depth such as a CPR depth meter 820. TheCPR depth meter 820 can be automatically displayed upon detection of CPRchest compressions.

On the CPR depth meter 820, depth bars 828 visually indicate the depthof the administered CPR compressions relative to a target depth 824. Assuch, the relative location of the depth bars 828 in relation to thetarget depth 824 can serve as a guide to a rescuer for controlling thedepth of CPR compressions. For example, depth bars 828 located in aregion 822 above the target depth bar 824 indicate that the compressionswere shallower than the target depth, and depth bars 828 located in aregion 826 below the target depth bar 824 indicate that the compressionswere deeper than the target depth. Again, then depth is inadequate(along with perhaps other factors) for a sufficient time to indicatethat the rescuer is fatiguing, an indicator to switch rescuers may beprovided in the manners discussed above.

While the example shown in FIG. 8A displayed the target depth 824 as asingle bar, in some additional examples, the target depth can bedisplayed as a range of preferred depths. For example, two bars 829 aand 829 b can be included on the depth meter 820 providing an acceptablerange of compression depths (e.g., as shown in FIG. 8B). Additionally,in some examples, compressions that have depths outside of an acceptablerange can be highlighted in a different color than compressions thathave depths within the acceptable range of compression depths.

The depth bars 828 displayed on the CPR depth meter 820 can representthe compression depths of the most recent CPR compressions administeredby the rescuer. For example, the CPR depth meter 820 can display depthbars 828 for the most recent 10-20 CPR compressions (e.g., the mostrecent 10 CPR compressions, the most recent 15 compressions, the mostrecent 20 CPR compressions). In another example, CPR depth meter 820 candisplay depth bars 828 for CPR compressions administered during aparticular time interval (e.g., the previous 10 seconds, the previous 20seconds).

In some additional embodiments, physiological information (e.g.,physiological information such as end-tidal CO2 information, arterialpressure information, volumetric CO2, pulse oximetry (presence ofamplitude of waveform possibly), and carotid blood flow (measured byDoppler) can be used to provide feedback on the effectiveness of the CPRdelivered at a particular target depth. Based on the physiologicalinformation, the system can automatically determine a target CPRcompression depth (e.g., calculate or look-up a new CPR compressiontarget depth) and provide feedback to a rescuer to increase or decreasethe depth of the CPR compressions. Thus, the system can provide bothfeedback related to how consistently a rescuer is administering CPRcompressions at a target depth, and feedback related to whether thetarget depth should be adjusted based on measured physiologicalparameters. If the rescuers does not respond to such feedback andcontinues performed sub-optimal CPR, the system may then display anadditional message to switch out the person performing CPR chestcompressions.

In some examples, the system regularly monitors and adjusts the targetCPR compression depth. In order to determine a desirable target depth,the system makes minor adjustments to the target CPR compression depthand observes how the change in compression depth affects the observedphysiological parameters before determining whether to make furtheradjustments to the target compression depth. More particularly, thesystem can determine an adjustment in the target compression depth thatis a fraction of an inch and prompt the rescuer to increase or decreasethe compression depth by the determined amount. For example, the systemcan adjust the target compression depth by 0.1-0.25 inches (e.g., 0.1inches to 0.15 inches, 0.15 to 0.25 inches, about 0.2 inches) andprovide feedback to the rescuer about the observed compression depthbased on the adjusted target compression depth. Then, over a set periodof time, the system can observe the physiological parameters and, basedon trends in the physiological parameters without making furtheradjustments to the target compression depth and at the end of the settime period, may determine whether to make further adjustments to thetarget compression depth.

And again, the actual performance of the rescuer against the revisedtarget may be continually monitored to determine when the rescuer'sperformance has fallen below an acceptable level, so that the rescuerand perhaps others may be notified to change who is performing the chestcompressions. Also, each of the relevant parameters of patient conditiondiscussed above with respect to the various screenshots may be made oneof multiple inputs to a process for determining when rescuers who areperforming one component of a rescue technique should be switched outwith another rescuer, such as for reasons of apparent fatigue on thepart of the first rescuer.

The particular devices and displays shown in FIGS. 5A-8B may beimplemented, as noted above, with a system that uses particulartechniques to improve the accuracy of a prediction that an applied shockwill be a success and that uses AMSA or other SPA values in making sucha prediction. For instance, the feedback provided by the displays in thefigures can be determined by selecting an appropriate ECG window sizefor calculating AMSA (e.g., one second or slightly longer, such as 1.5seconds or 2 seconds), a window type (e.g., Tukey), and particularcoefficients for the window. Such factors can also be changed over thetime of a VF event, as discussed above, so as to maintain a mostaccurate predictor of defibrillation success.

While at least some of the embodiments described above describetechniques and displays used during manual human-delivered chestcompressions, similar techniques and displays can be used with automatedchest compression devices such as the AUTOPULSE device manufactured byZOLL Medical Corporation of Chelmsford, Mass.

The particular techniques described here may be assisted by the use of acomputer-implemented medical device, such as a defibrillator thatincludes computing capability. Such defibrillator or other device isshown in FIG. 9, and may communicate with and/or incorporate a computersystem 900 in performing the operations discussed above, includingoperations for computing the quality of one or more components of CPRprovided to a victim and generating feedback to rescuers, includingfeedback to change rescuers who are performing certain components of theCPR. The system 900 may be implemented in various forms of digitalcomputers, including computerized defibrillators laptops, personaldigital assistants, tablets, and other appropriate computers.Additionally the system can include portable storage media, such as,Universal Serial Bus (USB) flash drives. For example, the USB flashdrives may store operating systems and other applications. The USB flashdrives can include input/output components, such as a wirelesstransmitter or USB connector that may be inserted into a USB port ofanother computing device.

The system 900 includes a processor 910, a memory 920, a storage device930, and an input/output device 940. Each of the components 910, 920,930, and 940 are interconnected using a system bus 950. The processor910 is capable of processing instructions for execution within thesystem 900. The processor may be designed using any of a number ofarchitectures. For example, the processor 910 may be a CISC (ComplexInstruction Set Computers) processor, a RISC (Reduced Instruction SetComputer) processor, or a MISC (Minimal Instruction Set Computer)processor.

In one implementation, the processor 910 is a single-threaded processor.In another implementation, the processor 910 is a multi-threadedprocessor. The processor 910 is capable of processing instructionsstored in the memory 920 or on the storage device 930 to displaygraphical information for a user interface on the input/output device940.

The memory 920 stores information within the system 900. In oneimplementation, the memory 920 is a computer-readable medium. In oneimplementation, the memory 920 is a volatile memory unit. In anotherimplementation, the memory 920 is a non-volatile memory unit.

The storage device 930 is capable of providing mass storage for thesystem 900. In one implementation, the storage device 930 is acomputer-readable medium. In various different implementations, thestorage device 930 may be a floppy disk device, a hard disk device, anoptical disk device, or a tape device.

The input/output device 940 provides input/output operations for thesystem 900. In one implementation, the input/output device 940 includesa keyboard and/or pointing device. In another implementation, theinput/output device 940 includes a display unit for displaying graphicaluser interfaces.

The features described can be implemented in digital electroniccircuitry, or in computer hardware, firmware, software, or incombinations of them. The apparatus can be implemented in a computerprogram product tangibly embodied in an information carrier, e.g., in amachine-readable storage device for execution by a programmableprocessor; and method steps can be performed by a programmable processorexecuting a program of instructions to perform functions of thedescribed implementations by operating on input data and generatingoutput. The described features can be implemented advantageously in oneor more computer programs that are executable on a programmable systemincluding at least one programmable processor coupled to receive dataand instructions from, and to transmit data and instructions to, a datastorage system, at least one input device, and at least one outputdevice. A computer program is a set of instructions that can be used,directly or indirectly, in a computer to perform a certain activity orbring about a certain result. A computer program can be written in anyform of programming language, including compiled or interpretedlanguages, and it can be deployed in any form, including as astand-alone program or as a module, component, subroutine, or other unitsuitable for use in a computing environment.

Suitable processors for the execution of a program of instructionsinclude, by way of example, both general and special purposemicroprocessors, and the sole processor or one of multiple processors ofany kind of computer. Generally, a processor will receive instructionsand data from a read-only memory or a random access memory or both. Theessential elements of a computer are a processor for executinginstructions and one or more memories for storing instructions and data.Generally, a computer will also include, or be operatively coupled tocommunicate with, one or more mass storage devices for storing datafiles; such devices include magnetic disks, such as internal hard disksand removable disks; magneto-optical disks; and optical disks. Storagedevices suitable for tangibly embodying computer program instructionsand data include all forms of non-volatile memory, including by way ofexample semiconductor memory devices, such as EPROM, EEPROM, and flashmemory devices; magnetic disks such as internal hard disks and removabledisks; magneto-optical disks; and CD-ROM and DVD-ROM disks. Theprocessor and the memory can be supplemented by, or incorporated in,ASICs (application-specific integrated circuits).

To provide for interaction with a user, the features can be implementedon a computer having an LCD (liquid crystal display) or LED display fordisplaying information to the user and a keyboard and a pointing devicesuch as a mouse or a trackball by which the user can provide input tothe computer.

The features can be implemented in a computer system that includes aback-end component, such as a data server, or that includes a middlewarecomponent, such as an application server or an Internet server, or thatincludes a front-end component, such as a client computer having agraphical user interface or an Internet browser, or any combination ofthem. The components of the system can be connected by any form ormedium of digital data communication such as a communication network.Examples of communication networks include a local area network (“LAN”),a wide area network (“WAN”), peer-to-peer networks (having ad-hoc orstatic members), grid computing infrastructures, and the Internet.

The computer system can include clients and servers. A client and serverare generally remote from each other and typically interact through anetwork, such as the described one. The relationship of client andserver arises by virtue of computer programs running on the respectivecomputers and having a client-server relationship to each other.

Many other implementations other than those described may be employed,and may be encompassed by the following claims.

What is claimed is:
 1. A system for managing care of a person receivingemergency cardiac assistance, the system comprising: one or morecapacitors for delivering a defibrillating shock to a patient; one ormore electronic ports for receiving signals from sensors for obtainingindications of an electrocardiogram (ECG) for the patient; and a patienttreatment module executable on one or more computer processors toidentify a phase in which a patient being monitored by the system is inrelative to a time at which an adverse cardiac event for patient began.2. The system of claim 1, wherein the phase in which the patient beingmonitored by the system is in comprises an elapsed time since theadverse cardiac event for the patient began.
 3. The system of claim 1,wherein the phase in which the patient being monitored by the system isin comprises a phase selected from an electrical, circulatory, andmetabolic phase.
 4. The system of claim 1, further comprising an outputmechanism arranged to indicate, to a user of the system, an indicationregarding the phase in which the patient is in.
 5. The system of claim4, wherein the output mechanism comprises a visual display, and thesystem is programmed to display to the user one indication of multiplepossible indications, wherein the one indication indicates to the userthe phase in which the patient is in.
 6. The system of claim 5, whereinthe system is programmed to display instructions for the user to carefor the patient, the instructions selected to correspond to the phase inwhich the patient is in.
 7. The system of claim 4, wherein the outputmechanism comprises an interlock that prevents a user from delivering ashock unless a determined likelihood of success of a shock reviving thepatient exceeds a determined value.
 8. The system of claim 1, whereinthe patient treatment module comprises an ECG analyzer for generating anamplitude spectrum area (AMSA) value.
 9. The system of claim 1, whereinthe patient treatment module comprises an ECG analyzer for generating anindication of heart rate for the patent.
 10. The system of claim 1,wherein the patient treatment module comprises an ECG analyzer forgenerating an indication of heart rate variability for the patent. 11.The system of claim 1, wherein the patient treatment module comprises anECG analyzer for generating an indication of ECG amplitude for thepatent.
 12. The system of claim 11, wherein the indication of ECGamplitude comprises an RMS measurement, measured peak-to-peak,peak-to-trough, or an average of peak-to-peak or peak-to-trough over aspecified interval
 13. The system of claim 1, wherein the patienttreatment module comprises an ECG analyzer for generating an indicationof a first derivative of ECG amplitude for the patent.
 14. The system ofclaim 1, wherein the patient treatment module comprises an ECG analyzerfor generating an indication of a second derivative of ECG amplitude forthe patent.
 15. The system of claim 1, where the patient treatmentmodule is programmed to determine whether a defibrillation shock, priorto a future defibrillation shock being consider for delivery, was atleast partially successful, and based at least in part on thedetermination of whether the prior defibrillation shock was at leastpartially successful, modifying a calculation of a likelihood of successfor delivering the future defibrillation shock.
 16. Acomputer-implemented method for managing care of a person receivingemergency cardiac assistance, the method comprising: monitoringelectrocardiogram (ECG) readings of the person using an electronicexternal defibrillator; identifying one or more values representative ofECG amplitude for the person; and indicating to an operator of themedical device a time since the person entered a state of needingmedical assistance, the indicating being based at least in part on theidentifying of one or more values representative of the ECG amplitudefor the person.
 17. The computer-implemented method of claim 16, whereinthe one or more values representative of ECG amplitude comprise one ormore amplitude spectrum area (AMSA) values.
 18. The computer-implementedmethod of claim 16, further comprising determining a combined value fora plurality of different values representative of ECG amplitude for theperson, and wherein the indication to the operator is based on thedetermined combined value.
 19. The computer-implemented method of claim16, wherein indicating to the operator of the medical device a timesince the person entered a state of needing medical assistance comprisesdisplaying an approximate elapsed time since the person enteredventricular fibrillation.
 20. The computer-implemented method of claim16, wherein indicating to the operator of the medical device a timesince the person entered a state of needing medical assistance comprisesdisplaying an identifier for a cardiac phase the person is in, whereinthe cardiac phase is selected from multiple different phases that arearranged timewise with respect to each other during a cardiac event.